Frontiers in endocrinology · 2022
The Construction and Analysis of Infiltrating Immune Cell and ceRNA Networks in Diabetic Foot Ulcer.
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Zeng Lin, Zhang Pengxiang, Fang Zebin, Liu Deliang, Li Huilin, Qu Xin, Chu Shufang, Zhao Hengxia, Liu Xuemei, Lee Maosheng
Аннотация
BACKGROUND: Diabetic foot ulcer (DFU) is a severe complication characterized by low-grade infectious inflammation and probably associated with specific competitive endogenous RNAs (ceRNAs) and infiltrating immune cells. Nonetheless, no reliable biomarkers are used for detecting infectious inflammation in DFU. Therefore, it is essential to explore potential biomarkers for the accurate diagnosis and treatment of DFU.
METHODS: The gene expression profile was retrieved from Gene Expression Omnibus (GEO) database and divided into two groups, namely, standard samples and DFU samples. To establish the ceRNA networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to analyze differential expression genes (DEGs). The cell type identification was achieved by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to screen-specific immune-infiltrating cells associated with DFU.
RESULTS: A ceRNA network was constructed with 20 differential expression circRNA (DEcircRNAs), 11 differential expression microRNAs (DEmiRNAs), and 9 differential expression mRNAs (DEmRNAs). Functional enrichment analysis demonstrated that DFU was mainly enriched in vascular endothelial growth factor (VEGF) and T-cell receptor signaling. In addition, CIBERSORT estimation indicated that CD8+ T cells and Monocytes were significantly related to the expression of IL-6, a DFU-specific infectious inflammation factor.
CONCLUSION: This study identified that some significant ceRNAs (JUNB, GATA3, hsa-circ-0049271 and hsa-circ-0074559) and infiltrating immune cells (CD8+ T cells and monocytes) might be related to DFU infectious inflammation.
METHODS: The gene expression profile was retrieved from Gene Expression Omnibus (GEO) database and divided into two groups, namely, standard samples and DFU samples. To establish the ceRNA networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to analyze differential expression genes (DEGs). The cell type identification was achieved by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to screen-specific immune-infiltrating cells associated with DFU.
RESULTS: A ceRNA network was constructed with 20 differential expression circRNA (DEcircRNAs), 11 differential expression microRNAs (DEmiRNAs), and 9 differential expression mRNAs (DEmRNAs). Functional enrichment analysis demonstrated that DFU was mainly enriched in vascular endothelial growth factor (VEGF) and T-cell receptor signaling. In addition, CIBERSORT estimation indicated that CD8+ T cells and Monocytes were significantly related to the expression of IL-6, a DFU-specific infectious inflammation factor.
CONCLUSION: This study identified that some significant ceRNAs (JUNB, GATA3, hsa-circ-0049271 and hsa-circ-0074559) and infiltrating immune cells (CD8+ T cells and monocytes) might be related to DFU infectious inflammation.